Application of the Information Measures to Input Support Selection in Functional Decomposition
Mariusz Rawski , L Jóźwiak , A. Chojnacki
AbstractGeneral functional decomposition has important application in many fields of modern engineering and science. Its practical usefulness for very complex systems is however limited by lack of an effective and efficient method for selection of the appropriate input supports for sub-systems. In this paper, an effective and efficient heuristic method for input support selection is proposed and discussed. The experimental results demonstrate that the method is able to construct optimal or near optimal supports efficiently even for large systems.
|Book||Polkowski Lech, Skowron Andrzej (eds.): Rough Sets and Current Trends in Computing, Lecture Notes In Computer Science, vol. LNAI 1424, 1998, Springer, ISBN 3-540-64655-8, 625 p., DOI:10.1007/3-540-69115-4|
|Keywords in English||Artificial Intelligence (incl. Robotics), Computation by Abstract Devices, Image Processing and Computer Vision, Mathematical Logic and Formal Languages|
|Citation count*||1 (2018-02-25)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.